Semillero R

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.title[
# Semillero R
]
.subtitle[
## Sesión 4: Visualización con R - Gráficos Complementarios
]
.institute[
### Universidad Nacional - Universidad de Antioquia
]
.date[
### 2022-12-03
]

---

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<center>
<h1> Exploración de datos</h1>
</center>

> *"El mayor valor de un gráfico es cuando nos obliga a notar lo que nunca esperábamos ver."* — John Tukey

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# [R Graph Gallery](https://www.r-graph-gallery.com/index.html)

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# [Data to Viz](https://www.data-to-viz.com/)

---
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# Miscelanea de gráficos

### Correlograma &#8594; [`corrplot`](https://cran.r-project.org/web/packages/corrplot/vignettes/corrplot-intro.html)

### Distribución Temporal &#8594; [`ggridges`](https://cran.r-project.org/web/packages/ggridges/vignettes/introduction.html)

### Coordenadas Paralelas &#8594; [`GGally`](https://ggobi.github.io/ggally/index.html)

### Series Temporales &#8594; [`dygraphs`](https://rstudio.github.io/dygraphs/index.html)

### Animaciones (gif) &#8594; [`gganimate`](https://gganimate.com/)

---
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# Correlograma &#8594; `corrplot`

```r
library(corrplot)
library(tidyverse)
iris %>% 
  select(where(is.numeric)) %>% 
  cor(method = "pearson") %>% 
  corrplot(
    method = "pie",
    tl.srt = 25,
    tl.col = "black",
    type = "lower",
    diag = FALSE
  )
```

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# Correlograma &#8594; `corrplot`

![](04-Visualization-p2_files/figure-html/unnamed-chunk-2-1.png)

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# Distribución Temporal &#8594; `ggridges`

```r
library(tidyverse)
library(lubridate)
library(ggridges)
library(tsibble)
AirPassengers %>% 
  as_tsibble() %>% 
  mutate(year = year(index),
         year = as_factor(year)) %>% 
  ggplot(mapping = aes(x = value, y = year)) +
  geom_density_ridges() +
  labs(x = "Pasajeros", y = "Año")
```

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# Distribución Temporal &#8594; `ggridges`

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# Coordenadas Paralelas &#8594; `GGally`

.pull-left[

```r
library(GGally)
ggparcoord(
  iris,
  columns = 1:4,
  groupColumn = 5,
  scale = "globalminmax",
  showPoints = TRUE,
  title = "Sin escalar",
  alphaLines = 0.3
)
```

]

.pull-right[

- Argumento **`scale`**<sup>1</sup>:
  - globalminmax
  - uniminmax
  - std
  - center

]

.foot-note[
[1][Feature Scaling- Wikipedia.](https://en.wikipedia.org/wiki/Feature_scaling)
]

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# Coordenadas Paralelas &#8594; `GGally`

---
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# Series Temporales &#8594; `dygraphs`

- [Casos positivos de COVID-19 en Colombia](https://www.datos.gov.co/Salud-y-Protecci-n-Social/Casos-positivos-de-COVID-19-en-Colombia/gt2j-8ykr)

```r
# Depuración y estructuración para ejemplo
library(tidyverse)
library(lubridate)
library(janitor)

datos <- read_csv("Casos_positivos_de_COVID-19_en_Colombia.csv")

prueba <- datos %>% 
  clean_names() %>% 
  mutate(nueva_fecha = as_date(fecha_de_notificacion, format = "%d/%m/%Y"),
         sexo = str_to_upper(sexo)) %>% 
  count(nueva_fecha, sexo) %>% 
  filter(nueva_fecha != "2021-04-18")

write_rds(prueba, file = "covid_sexos.rds", compress = "xz")
```

---
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# Series Temporales &#8594; `dygraphs`

- [Descargar datos](/Actividades/2021_01/data/covid_sexos.rds)

```r
library(xts)
library(dygraphs)
library(tidyverse)
prueba <- read_rds("data/covid_sexos.rds")

mujeres <- prueba %>% filter(sexo == "F")
hombres <- prueba %>% filter(sexo == "M")

prueba_mujeres <- xts(x = mujeres$n, order.by = mujeres$nueva_fecha)
prueba_hombres <- xts(x = hombres$n, order.by = hombres$nueva_fecha)
ambos <- cbind(Mujeres = prueba_mujeres, Hombres =  prueba_hombres)
dygraph(ambos, width = 700, height = 350) %>% dyRangeSelector()
```

---
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# Series Temporales &#8594; `dygraphs`

<div id="htmlwidget-446c7103836d427bdd1c" style="width:700px;height:400px;" class="dygraphs html-widget"></div>
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---
class: middle

# Animaciones (gif) &#8594; `gganimate`

```r
library(tidyverse); library(gganimate); library(janitor); library(viridis)

ejemplo <- read_csv(
  "data/Tasas_de_homicidios_seg_n_municipios_por_cien_mil_habitantes._A_os_1990_-_2017.csv"
) %>% 
  pivot_longer(cols = -Municipio, names_to = "year",
               values_to = "homicidios",
               names_transform = list(year = as.numeric)) %>% 
  clean_names()

ejemplo %>%
  filter(municipio %in% c("Armenia", "Salento", "Montenegro")) %>% 
  ggplot(aes(x = year, y = homicidios, group = municipio, color = municipio)) +
  geom_line() +
  geom_point() +
  scale_color_viridis(discrete = TRUE) +
  labs(x = "Año", y = "Homicidios",
       title = "Homicidios departamento del Quindío") +
  transition_reveal(year)

anim_save("ejemplo.gif")
```

---
class: middle

# Animaciones (gif) &#8594; `gganimate`